Alternatives to Codacy logo

Alternatives to Codacy

SonarQube, Code Climate, Better Code Hub, Codecov, and Coveralls are the most popular alternatives and competitors to Codacy.
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What is Codacy and what are its top alternatives?

Codacy automates code reviews to improve and standardize code quality across large enterprises. It identifies issues through static code analysis. Integrates with GitLab, GitHub & Bitbucket.
Codacy is a tool in the Code Review category of a tech stack.

Top Alternatives to Codacy

  • SonarQube

    SonarQube

    SonarQube provides an overview of the overall health of your source code and even more importantly, it highlights issues found on new code. With a Quality Gate set on your project, you will simply fix the Leak and start mechanically improving. ...

  • Code Climate

    Code Climate

    After each Git push, Code Climate analyzes your code for complexity, duplication, and common smells to determine changes in quality and surface technical debt hotspots. ...

  • Better Code Hub

    Better Code Hub

    Better Code Hub runs the first analysis of any GitHub repository with the default configuration. This default configuration is based on the programming languages reported by GitHub and supported by Better Code Hub. Better Code Hub further uses heuristics and commonly used conventions. ...

  • Codecov

    Codecov

    Our patrons rave about our elegant coverage reports, integrated pull request comments, interactive commit graphs, our Chrome plugin and security. ...

  • Coveralls

    Coveralls

    Coveralls works with your CI server and sifts through your coverage data to find issues you didn't even know you had before they become a problem. Free for open source, pro accounts for private repos, instant sign up with GitHub OAuth. ...

  • codebeat

    codebeat

    codebeat helps you prioritize issues and identify quick wins. It provides immediate and continuous feedback on complexity and duplication ...

  • ESLint

    ESLint

    A pluggable and configurable linter tool for identifying and reporting on patterns in JavaScript. Maintain your code quality with ease. ...

  • Prettier

    Prettier

    Prettier is an opinionated code formatter. It enforces a consistent style by parsing your code and re-printing it with its own rules that take the maximum line length into account, wrapping code when necessary. ...

Codacy alternatives & related posts

related SonarQube posts

Simon Reymann
Senior Fullstack Developer at QUANTUSflow Software GmbH | 27 upvotes 路 1.8M views

Our whole DevOps stack consists of the following tools:

  • GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
  • Respectively Git as revision control system
  • SourceTree as Git GUI
  • Visual Studio Code as IDE
  • CircleCI for continuous integration (automatize development process)
  • Prettier / TSLint / ESLint as code linter
  • SonarQube as quality gate
  • Docker as container management (incl. Docker Compose for multi-container application management)
  • VirtualBox for operating system simulation tests
  • Kubernetes as cluster management for docker containers
  • Heroku for deploying in test environments
  • nginx as web server (preferably used as facade server in production environment)
  • SSLMate (using OpenSSL) for certificate management
  • Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
  • PostgreSQL as preferred database system
  • Redis as preferred in-memory database/store (great for caching)

The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:

  • Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
  • Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
  • Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
  • Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
  • Scalability: All-in-one framework for distributed systems.
  • Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
See more
Ganesa Vijayakumar
Full Stack Coder | Module Lead | 18 upvotes 路 1.9M views

I'm planning to create a web application and also a mobile application to provide a very good shopping experience to the end customers. Shortly, my application will be aggregate the product details from difference sources and giving a clear picture to the user that when and where to buy that product with best in Quality and cost.

I have planned to develop this in many milestones for adding N number of features and I have picked my first part to complete the core part (aggregate the product details from different sources).

As per my work experience and knowledge, I have chosen the followings stacks to this mission.

UI: I would like to develop this application using React, React Router and React Native since I'm a little bit familiar on this and also most importantly these will help on developing both web and mobile apps. In addition, I'm gonna use the stacks JavaScript, jQuery, jQuery UI, jQuery Mobile, Bootstrap wherever required.

Service: I have planned to use Java as the main business layer language as I have 7+ years of experience on this I believe I can do better work using Java than other languages. In addition, I'm thinking to use the stacks Node.js.

Database and ORM: I'm gonna pick MySQL as DB and Hibernate as ORM since I have a piece of good knowledge and also work experience on this combination.

Search Engine: I need to deal with a large amount of product data and it's in-detailed info to provide enough details to end user at the same time I need to focus on the performance area too. so I have decided to use Solr as a search engine for product search and suggestions. In addition, I'm thinking to replace Solr by Elasticsearch once explored/reviewed enough about Elasticsearch.

Host: As of now, my plan to complete the application with decent features first and deploy it in a free hosting environment like Docker and Heroku and then once it is stable then I have planned to use the AWS products Amazon S3, EC2, Amazon RDS and Amazon Route 53. I'm not sure about Microsoft Azure that what is the specialty in it than Heroku and Amazon EC2 Container Service. Anyhow, I will do explore these once again and pick the best suite one for my requirement once I reached this level.

Build and Repositories: I have decided to choose Apache Maven and Git as these are my favorites and also so popular on respectively build and repositories.

Additional Utilities :) - I would like to choose Codacy for code review as their Startup plan will be very helpful to this application. I'm already experienced with Google CheckStyle and SonarQube even I'm looking something on Codacy.

Happy Coding! Suggestions are welcome! :)

Thanks, Ganesa

See more

related Code Climate posts

Jerome Dalbert
Senior Backend Engineer at StackShare | 5 upvotes 路 381.9K views

The continuous integration process for our Rails backend app starts by opening a GitHub pull request. This triggers a CircleCI build and some Code Climate checks.

The CircleCI build is a workflow that runs the following jobs:

  • check for security vulnerabilities with Brakeman
  • check code quality with RuboCop
  • run RSpec tests in parallel with the knapsack gem, and output test coverage reports with the simplecov gem
  • upload test coverage to Code Climate

Code Climate checks the following:

  • code quality metrics like code complexity
  • test coverage minimum thresholds

The CircleCI jobs and Code Climate checks above have corresponding GitHub status checks.

Once all the mandatory GitHub checks pass and the code+functionality have been reviewed, developers can merge their pull request into our Git master branch. Code is then ready to deploy!

#ContinuousIntegration

See more
Better Code Hub logo

Better Code Hub

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Actionable code quality feedback on each commit
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+ 1
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PROS OF BETTER CODE HUB
    No pros available
    CONS OF BETTER CODE HUB
      No cons available

      related Better Code Hub posts

      related Codecov posts

      Tim Abbott
      Shared insights
      on
      Codecov
      Coveralls
      at

      We use Codecov because it's a lot better than Coveralls. Both of them provide the useful feature of having nice web-accessible reports of which files have what level of test coverage (though every coverage tool produces reasonably nice HTML in a directory on the local filesystem), and can report on PRs cases where significant new code was added without test coverage.

      That said, I'm pretty unhappy with both of them for our use case. The fundamental problem with both of them is that they don't handle the ~1% probability situations with missing data due to networking flakiness well. The reason I think our use case is relevant is that we submit coverage data from multiple jobs (one that runs our frontend test suite and another that runs our backend test suite), and the coverage provider is responsible for combining that data together.

      I think the problem is if a test suite runs successfully but due to some operational/networking error between Travis/CircleCI and Codecov the coverage data for part of the codebase doesn't get submitted, Codecov will report a huge coverage drop in a way that is very confusing for our contributors (because they experience it as "why did the coverage drop 12%, all I did was added a test").

      We migrated from Coveralls to Codecov because empirically this sort of breakage happened 10x less on Codecov, but it still happens way more often than I'd like.

      I wish they put more effort in their retry mechanism and/or providing clearer debugging information (E.g. a big "Missing data" banner) so that one didn't need to be specifically told to ignore Codecov/Coveralls when it reports a giant coverage drop.

      See more
      Shared insights
      on
      Codecov
      Coveralls

      Codecov Although I actually use both codecov and Coveralls, I very much like the graphs I get from codecov, and some of their diagnostic tools.

      See more
      Coveralls logo

      Coveralls

      381
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      Track your project's code coverage over time, changes to files, and badge your GitHub repo
      381
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      related Coveralls posts

      Tim Abbott
      Shared insights
      on
      Codecov
      Coveralls
      at

      We use Codecov because it's a lot better than Coveralls. Both of them provide the useful feature of having nice web-accessible reports of which files have what level of test coverage (though every coverage tool produces reasonably nice HTML in a directory on the local filesystem), and can report on PRs cases where significant new code was added without test coverage.

      That said, I'm pretty unhappy with both of them for our use case. The fundamental problem with both of them is that they don't handle the ~1% probability situations with missing data due to networking flakiness well. The reason I think our use case is relevant is that we submit coverage data from multiple jobs (one that runs our frontend test suite and another that runs our backend test suite), and the coverage provider is responsible for combining that data together.

      I think the problem is if a test suite runs successfully but due to some operational/networking error between Travis/CircleCI and Codecov the coverage data for part of the codebase doesn't get submitted, Codecov will report a huge coverage drop in a way that is very confusing for our contributors (because they experience it as "why did the coverage drop 12%, all I did was added a test").

      We migrated from Coveralls to Codecov because empirically this sort of breakage happened 10x less on Codecov, but it still happens way more often than I'd like.

      I wish they put more effort in their retry mechanism and/or providing clearer debugging information (E.g. a big "Missing data" banner) so that one didn't need to be specifically told to ignore Codecov/Coveralls when it reports a giant coverage drop.

      See more
      Shared insights
      on
      Codecov
      Coveralls

      Codecov Although I actually use both codecov and Coveralls, I very much like the graphs I get from codecov, and some of their diagnostic tools.

      See more
      codebeat logo

      codebeat

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      Automated code review for Swift
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      PROS OF CODEBEAT
        No pros available
        CONS OF CODEBEAT
          No cons available

          related codebeat posts

          It is very important to have clean code. To be sure that the code quality is not really bad I use a few tools. I love SonarQube with many relevant hints and deep analysis of code. codebeat isn't so detailed, but it can find complexity issues and duplications. Codacy cannot find more bugs then your IDE. The winner for me is SonarQube that shows me really relevant bugs in my code.

          See more
          ESLint logo

          ESLint

          9.7K
          5.5K
          21
          The fully pluggable JavaScript code quality tool
          9.7K
          5.5K
          + 1
          21

          related ESLint posts

          Simon Reymann
          Senior Fullstack Developer at QUANTUSflow Software GmbH | 27 upvotes 路 1.8M views

          Our whole DevOps stack consists of the following tools:

          • GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
          • Respectively Git as revision control system
          • SourceTree as Git GUI
          • Visual Studio Code as IDE
          • CircleCI for continuous integration (automatize development process)
          • Prettier / TSLint / ESLint as code linter
          • SonarQube as quality gate
          • Docker as container management (incl. Docker Compose for multi-container application management)
          • VirtualBox for operating system simulation tests
          • Kubernetes as cluster management for docker containers
          • Heroku for deploying in test environments
          • nginx as web server (preferably used as facade server in production environment)
          • SSLMate (using OpenSSL) for certificate management
          • Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
          • PostgreSQL as preferred database system
          • Redis as preferred in-memory database/store (great for caching)

          The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:

          • Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
          • Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
          • Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
          • Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
          • Scalability: All-in-one framework for distributed systems.
          • Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
          See more
          Johnny Bell
          Software Engineer at Weedmaps | 18 upvotes 路 1M views

          So when starting a new project you generally have your go to tools to get your site up and running locally, and some scripts to build out a production version of your site. Create React App is great for that, however for my projects I feel as though there is to much bloat in Create React App and if I use it, then I'm tied to React, which I love but if I want to switch it up to Vue or something I want that flexibility.

          So to start everything up and running I clone my personal Webpack boilerplate - This is still in Webpack 3, and does need some updating but gets the job done for now. So given the name of the repo you may have guessed that yes I am using Webpack as my bundler I use Webpack because it is so powerful, and even though it has a steep learning curve once you get it, its amazing.

          The next thing I do is make sure my machine has Node.js configured and the right version installed then run Yarn. I decided to use Yarn because when I was building out this project npm had some shortcomings such as no .lock file. I could probably move from Yarn to npm but I don't really see any point really.

          I use Babel to transpile all of my #ES6 to #ES5 so the browser can read it, I love Babel and to be honest haven't looked up any other transpilers because Babel is amazing.

          Finally when developing I have Prettier setup to make sure all my code is clean and uniform across all my JS files, and ESLint to make sure I catch any errors or code that could be optimized.

          I'm really happy with this stack for my local env setup, and I'll probably stick with it for a while.

          See more
          Prettier logo

          Prettier

          1.2K
          337
          0
          Prettier is an opinionated code formatter.
          1.2K
          337
          + 1
          0
          PROS OF PRETTIER
            No pros available
            CONS OF PRETTIER
              No cons available

              related Prettier posts

              Simon Reymann
              Senior Fullstack Developer at QUANTUSflow Software GmbH | 27 upvotes 路 1.8M views

              Our whole DevOps stack consists of the following tools:

              • GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
              • Respectively Git as revision control system
              • SourceTree as Git GUI
              • Visual Studio Code as IDE
              • CircleCI for continuous integration (automatize development process)
              • Prettier / TSLint / ESLint as code linter
              • SonarQube as quality gate
              • Docker as container management (incl. Docker Compose for multi-container application management)
              • VirtualBox for operating system simulation tests
              • Kubernetes as cluster management for docker containers
              • Heroku for deploying in test environments
              • nginx as web server (preferably used as facade server in production environment)
              • SSLMate (using OpenSSL) for certificate management
              • Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
              • PostgreSQL as preferred database system
              • Redis as preferred in-memory database/store (great for caching)

              The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:

              • Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
              • Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
              • Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
              • Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
              • Scalability: All-in-one framework for distributed systems.
              • Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
              See more
              Johnny Bell
              Software Engineer at Weedmaps | 18 upvotes 路 1M views

              So when starting a new project you generally have your go to tools to get your site up and running locally, and some scripts to build out a production version of your site. Create React App is great for that, however for my projects I feel as though there is to much bloat in Create React App and if I use it, then I'm tied to React, which I love but if I want to switch it up to Vue or something I want that flexibility.

              So to start everything up and running I clone my personal Webpack boilerplate - This is still in Webpack 3, and does need some updating but gets the job done for now. So given the name of the repo you may have guessed that yes I am using Webpack as my bundler I use Webpack because it is so powerful, and even though it has a steep learning curve once you get it, its amazing.

              The next thing I do is make sure my machine has Node.js configured and the right version installed then run Yarn. I decided to use Yarn because when I was building out this project npm had some shortcomings such as no .lock file. I could probably move from Yarn to npm but I don't really see any point really.

              I use Babel to transpile all of my #ES6 to #ES5 so the browser can read it, I love Babel and to be honest haven't looked up any other transpilers because Babel is amazing.

              Finally when developing I have Prettier setup to make sure all my code is clean and uniform across all my JS files, and ESLint to make sure I catch any errors or code that could be optimized.

              I'm really happy with this stack for my local env setup, and I'll probably stick with it for a while.

              See more